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Calocybe indica, generally referred as milky mushroom, is one of the edible mushroom species suitable for cultivation in the tropical and sub-tropical regions of the world. However, lack of potential high yielding strains has limited its wider adaptability. To overcome this limitation, in this study, the germplasms of C. indica from different geographical regions of India were characterized based on their morphological, molecular and agronomical attributes. Internal transcribed spacers (ITS1 and ITS4)-based PCR amplification, sequencing and nucleotide analysis confirmed the identity of all the studied strains as C. indica. Further, evaluation of these strains for morphological and yield parameters led to the identification of eight high yielding strains in comparison to the control (DMRO-302). Moreover, genetic diversity analysis of these thirty-three strains was performed using ten sequence-related amplified polymorphism (SRAP) markers/combinations. The Unweighted Pair-group Method with Arithmetic Averages (UPGMA)-based phylogenetic analysis categorized the thirty-three strains along with the control into three clusters. Cluster I possesses the maximum number of strains. Among the high yielding strains, high antioxidant activity and phenol content was recorded in DMRO-54, while maximum protein content was observed in DMRO-202 and DMRO-299 as compared with the control strain. The outcome of this study will help the mushroom breeders and growers in commercializing C. indica. [ABSTRACT FROM AUTHOR]

The lower course of the Damodar River in West Bengal is one of the most polluted stretches in the Ganga River basin. There is a lack of research along the whole course of the Damodar, and parameter level analysis receives little attention. Eleven monitoring sites were chosen based on the potential sources of pollution for 6 years (2014–2019). Multivariate statistical techniques (factor analysis (FA), cluster analysis (CA), and discriminate analysis (DA)) evaluate the spatial and temporal variation of Damodar River water quality by considering 24 parameters. Factor analysis extracts the most influential seasonal parameters, and stepwise DA extracts ammonia, DO, potassium, temperature, total coliform, TFS, and turbidity, which are the most responsible parameters for seasonal variation of the water quality. CA classify sampling stations into three groups helping to identify the spatial variation of water quality. Ammonia, BOD, calcium, chloride, conductivity, DO, sodium, sulfate, temperature, Alkalinity, TDS, hardness, TSS, and turbidity are the most influential variables for spatial variation extracted through stepwise DA. Monsoon season shows a higher pollution level due to the contribution from both point and non-point sources. Due to high-density urban areas and large-scale industries, the middle course is more polluted. The Canadian Council of Ministers of the Environment (CCME) water quality index (WQI) accesses the water quality in temporal and spatial scales. The resultant water quality pattern is matched with the derived result from multivariate analysis. Poor water quality is regular at all sample sites in all seasons. [ABSTRACT FROM AUTHOR]

Religious sites in Braj Mandal, India are visited by millions of pilgrims throughout the year. To meet the growing needs of pilgrims, rapid urbanisation is taking place with the result that there is change in the ancient spatial configuration. This research aims to explore the desired environmental ambiance for enhancing devotional ecstasy. The spatial configuration has been documented through physical mapping and visual preferences have been identified via a pilgrim opinion survey. Conclusions have been drawn regarding the identification of parameters of spatial configuration that enhance the environmental ambience for devotional ecstasy. [ABSTRACT FROM AUTHOR]

Default values for many parameters in Numerical Weather Prediction models are typically adopted based on theoretical or experimental investigations by scheme designers. Short‐range forecasts are substantially affected by the specification of parameters in the Weather Research and Forecasting (WRF) model. The presence of a multitude of parameters and several output variables in the WRF model renders appropriate parameter value identification quite challenging. This study aims to identify the parameters that most strongly influence the model output variables using a Global Sensitivity Analysis (GSA) method. Morris One‐At‐a‐Time (MOAT), a GSA method, is used to identify the sensitivities of 23 chosen tunable parameters corresponding to seven physical parameterization schemes of the WRF model. The sensitivity measures (MOAT mean and standard deviation) are evaluated for 11 output variables simulated by the WRF model, corresponding to different parameters. Twelve high‐intensity 4‐day precipitation events during the Indian summer monsoon during 2015, 2016, and 2017 over India's monsoon core region are considered for the study. Though the parameter sensitivities vary depending on the model output variable, overall results suggest a general trend. The consistency of sensitivity analysis results with different initial and lateral boundary conditions is also assessed. Key Points: Sensitivities of 23 chosen tunable model parameters are evaluatedNine parameters exert a significant influence on the output variablesSensitivity analysis results are consistent with different initial and lateral boundary conditions [ABSTRACT FROM AUTHOR]

Out of many parameters for human identification, stature is a principal anatomical variable. Stature estimation, especially in post-mortem cases where only some parts of an individual is available or cases where only footprints are available, foot anthropometry will be extremely useful. The objective of the current study is to find out interrelationship between the stature & foot length & formulating a regression equation for determination of height from foot length among individuals from Central India. This cross sectional study was conducted at the department of Forensic Medicine & Toxicology of Datta Meghe Medical College, Nagpur from June 2020 to August 2020. Collected data was entered in Microsoft Excel sheet & analysed using SPSS software. Mean stature in male was 165.8 cm with SD of 6 cm, while in female, it was 159.9 cm with SD of 6.7 cm. Gender wise difference in mean stature & foot length was statistically significant. This research found remarkable positive correlation between stature & foot-length in both sexes. Regression formula was derived which will be extremely helpful to forecast the height of an individual from known foot-length in cases of medicolegal importance. [ABSTRACT FROM AUTHOR]

World across, there is an increasing concern about river health. In India, Ganga River Basin Management Plan (GRBMP) 2015 considered River Ganga as an ecological entity. This paper attempts to present a framework for river health assessment in India and discusses its applicability for River Ganga near Varanasi. In the proposed framework, the River Health Condition (RHC) is assessed through the calculation of River Health Index (RHI) on a 0-100 scale and categorized as Acceptable or Poor. RHI is calculated by using selected parameters/indices normalized on the 0-5 scale based on their critical and target values. River Health is presented through a coloured circumscribed pentagon each of whose side represents one of five indicator groups: i. Organo-electrolytic-bacterial qualities. ii. Nutrients, iii. Algae, iv. Macroinvertebrates, and v. Fish. Application of the proposed framework has been tested and explained using observed data for four seasons per year for two years from five locations of River Ganga near Varanasi. The colour of circumscribing pentagon reflects overall river health condition at a given location and each side of pentagon reflects health score concerningto one indicator group. The analyses indicate that the health of River Ganga near Varanasi is improving with time. The river health is found at its best level during Spring season and unstable during Post Monsoon period at most of the locations. The severely reduced RHI indicate “Overstressed” condition of River Ganga at the confluence points of River Assi and Varuna, which are evidenced by the presence of pollution tolerant biotic species. There are clear stretches of the river near outfall points which are nutrients rich and organically polluted causing poor health of river showing a disturbed balance of biotic species. Indicator group score based RHI gives a clear identification of critical parameters which may be used in strategic planning for river health restoration. [ABSTRACT FROM AUTHOR]

A challenge to the analysis of corporate governance lies in a large number of variables that define and shape it, and hence, identification of the key parameters improves the effectiveness of overall governance. This paper aims at the identification of key governance parameters of scheduled Urban Cooperative Banks (UCBs) in India through an empirical analysis. The quest for key governance parameters in this paper culminates in eight parameters, encompassing three core features, namely, members' participation, technically qualified and trained directors, and a system of accountability. Identification of these core governance features is the main finding of this paper. These core features, through their subtle influence, take care of the remaining aspects of the governance structure of scheduled UCBs and are useful not only for timely red-flagging in the supervisory processes but also for strengthening the governance of cooperative banks in India. [ABSTRACT FROM AUTHOR]

Introduction: Anthropology plays an important role in various medicolegal aspects; apart from determination of Age, Sex and Race of individual, stature is also one of the important parameter of identification various civil and criminal cases. Therefore efforts have been made to determine association between stature and length of clavicle if any.Materials and Method: The present research was carried out in department of Anatomy JNMC Sawangi (M) Wardha; was conducted on total 50 Female individual of age 17–24. The length was calculated with the help of osteometric callipers for clavicles from anatomical landmarks and stature was calculated in centimetres.Conclusion. From present research it was concluded that the length of clavicle and stature reveals positive correlation and the linear relationship between the living stature and length of clavicle of each side was carried out in the form of regression equation. [ABSTRACT FROM AUTHOR]

Hydrological models demand large numbers of input parameters, which are to be optimally identified for better simulation of various hydrological processes. Identifying the most relevant parameters and their values using efficient sensitivity analysis methods helps to better understand model performance. In this study, the physically-based distributed model SHETRAN is used for hydrological simulation on the Netravathi River Basin in south India and the most important parameters are identified using the Morris screening method. Further, the influence of a particular model parameter on streamflow is quantified using local sensitivity analysis and optimal parameters are obtained for calibration of the SHETRAN model. The results demonstrate the capability of two-stage sensitivity analysis, combining qualitative and quantitative methods in the initial screening-out of insignificant model parameters, identifying parameter interactions and quantifying the contribution of each model parameter to the streamflow. The results of the sensitivity analysis simplified the calibration procedure of SHETRAN for the study area. [ABSTRACT FROM AUTHOR]